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Item #:
85336271
Artificial Intelligence for Robotics: Build intelligent robots using ROS 2, Python, OpenCV, and AI/ML techniques for real-world tasks
Item #:
85336271
BZD 132
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What Stands Out
Comprehensive Guide
This second edition offers an extensive, clear roadmap for integrating AI into robotics, making complex subjects accessible to learners and practitioners alike.
Hands-On Projects
Includes practical projects using ROS 2, Python, and OpenCV, empowering readers to develop real-world robotic applications and enhancing their skill set effectively.
Updated Techniques
Covers the latest advancements in AI and ML, ensuring that users stay ahead of the technology curve while implementing innovative solutions in robotics.
Product Details
| Item Weight | 1.5 lbs (680 grams) |
Who Should Buy?
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Aspiring Robotics Engineers
Perfect for individuals pursuing a career in robotics, providing essential skills and knowledge in AI and programming.
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Academic Students
Ideal for students studying robotics or computer science, offering practical applications of AI techniques in real-world scenarios.
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Hobbyist Makers
Great for enthusiasts looking to build personal projects, combining ROS 2 and AI to create innovative robotic applications.
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Absolute Beginners
Not suitable for those without any programming or robotics background; the material may be too complex to grasp.
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Non-Technical Users
Users without a technical inclination or interest in coding will find the subject matter challenging and unenjoyable.
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Focused Hobbyists
Individuals interested in niche robotics or specific applications might not find general AI/ML techniques broadly applicable.
Product Description
Artificial Intelligence for Robotics: Build intelligent robots using ROS 2, Python, OpenCV, and AI/ML techniques for real-world tasks
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Customer Questions & Answers
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Question:
What are the main topics covered in 'Artificial Intelligence for Robotics' 2nd Edition?
Answer: This edition explores a range of crucial topics including ROS 2 (Robot Operating System), Python programming for robotic applications, OpenCV for computer vision, and AIML techniques for machine learning. Each section is designed to provide insights into building intelligent robots capable of performing complex real-world tasks. The book emphasizes practical applications, enabling readers to understand how to implement these technologies in real scenarios, such as robotics competitions, research projects, or personal automation systems. -
Question:
Is prior programming knowledge required to understand this book?
Answer: While having a background in programming, particularly Python, can be beneficial, it is not strictly necessary. The book is structured to cater to a wide range of skill levels, providing foundational concepts before diving into more advanced topics. Beginners can grasp the essential principles of robotics and AI, while seasoned developers can deepen their understanding and explore advanced techniques. Real-world examples help bridge the gap, making it easier for readers to apply what they learn practically. -
Question:
How does this book approach the integration of AI with robotics?
Answer: The book offers a comprehensive approach to integrating AI into robotics by discussing various frameworks and methodologies. It covers how ROS 2 serves as the backbone for robot programming, while AIML techniques are introduced to enable robots to learn from data and adapt to their environments. This synergy allows robots not just to execute programmed tasks but to make decisions based on inputs. Real-world scenarios, such as autonomous navigation or facial recognition systems, illustrate the power of AI in enhancing robotic functionalities. -
Question:
Can this book help me with a specific robotics project?
Answer: Absolutely! This book is structured to support individuals working on specific robotics projects by guiding them through practical implementations. Each chapter focuses on real-world tasks, addressing common challenges encountered in robotics, like perception and decision-making. By following along, readers can apply the concepts directly to their projects, whether building a robotic arm, a drone, or engaging in more complex systems like robotic assistants in smart homes. -
Question:
What is the target audience for 'Artificial Intelligence for Robotics'?
Answer: The target audience encompasses a broad spectrum of readers, including students in coding or engineering disciplines, professional developers looking to enhance their skill set, and hobbyists interested in robotics. The book's clear explanations and practical examples make it suitable for beginners while still offering valuable insights for advanced practitioners. Whether you’re embarking on a robotics career or exploring personal projects, this resource is designed to meet a variety of learning needs. -
Question:
Does the book include code examples for practical learning?
Answer: Yes, 'Artificial Intelligence for Robotics' provides numerous code examples throughout its chapters. These examples serve to reinforce the concepts discussed, allowing readers to see theory in action. Moreover, they include both snippets and complete programs that utilize ROS 2, Python, and OpenCV. This hands-on approach enables readers to replicate projects, troubleshoot their code, and confidently experiment as they learn, enhancing their practical coding skills in robotics. -
Question:
What does ROS 2 offer for robotics development?
Answer: ROS 2 is an advanced robot operating system that significantly enhances robotics development by providing a robust framework for building complex robotic systems. It supports real-time capabilities and is designed for distributed systems, making it suitable for various applications, including industrial, service, and personal robotics. The book thoroughly explains how to leverage ROS 2 features to create and manage robot behaviors, ensuring effective communication between different robot components and fostering smoother operation in challenging environments. -
Question:
Can this book help in learning computer vision techniques?
Answer: Yes, the book dedicates a section to computer vision techniques using OpenCV, which is integral for many robotics applications. It explains core concepts like image processing, object detection, and feature extraction in a straightforward manner. Readers will learn how to integrate visual perception capabilities into robotics, enabling robots to interpret their surroundings effectively. Practical examples include building systems that recognize objects and track movements, essential for tasks like autonomous driving or interactive robotic applications. -
Question:
Are there any prerequisites for using the AI and machine learning techniques discussed?
Answer: While prior knowledge of machine learning can be helpful, the book is structured to introduce readers to foundational concepts first. It covers essential topics in AIML, guiding readers step-by-step through the implementation processes. Practical use cases such as chatbot development or AI-driven decision systems illustrate how to apply these techniques in robotics. This makes it accessible to beginners while still providing depth for those with a more advanced understanding seeking to refine their skills. -
Question:
Where can I buy 'Artificial Intelligence for Robotics' 2nd Edition in Belize?
Answer: You can purchase 'Artificial Intelligence for Robotics: Build intelligent robots using ROS 2, Python, OpenCV, and AIML techniques for real-world tasks 2nd Edition' from Ubuy. Ubuy offers a range of products, and this book is available for order directly through their platform, ensuring a seamless shopping experience. With its user-friendly interface and comprehensive service, Ubuy is a reliable choice for acquiring this essential resource for your robotics studies.
Robotics & Automation Editorial Review
**** "Artificial Intelligence for Robotics: Build intelligent robots using ROS 2, Python, OpenCV, and AIML techniques for real-world tasks, 2nd Edition" emerges as a leading resource in robotics literature, particularly for those looking to merge AI with practical robotic applications. The author, Govers, an established figure in the field, presents an engaging and comprehensive guide that amalgamates various robotics disciplines, providing readers with a clear path to creating robots using modern machine learning techniques. The book's strong practical focus shines through, with clear instructions, abundant illustrations, and code examples that promise to guide readers through the complexities of robot building. By addressing critical topics such as computer vision, object recognition, genetic algorithms, and decision-making theory, it not only provides foundational knowledge but also leans into AI's significance in robotics. This multidisciplinary approach fosters a deeper understanding and allows for greater applicability of the concepts discussed. However, despite its many strengths, readers have noted some significant challenges. While the theoretical foundation is solid, the practical application can be daunting, even for those with intermediate to advanced skills. An outdated GitHub repository and discrepancies in the parts list hinder the Construction process, leading to frustration among users who expected a more streamlined building experience. Moreover, some coding examples fail to align with the latest ROS 2 standards, requiring readers to invest additional effort to adapt older code. While the content is undoubtedly valuable, Prospective readers should be prepared for a steep learning curve, particularly if they are new to robotics. The Considerable setup requirements and the need for troubleshooting could deter some. That said, the book's focus on AI applications in robotics makes it a compelling read for those who are ready to tackle the intricacies involved. In sum, while the book serves as an excellent academic resource for both beginners and intermediate learners entranced by the Prospect of building intelligent robots, one must proceed with an understanding of the potential challenges in practical application. **
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Pros
- Comprehensive coverage of robotics topics including computer vision, genetic algorithms, and AI.
- Clear explanations and practical approach with detailed instructions and illustrations.
- Encourages understanding through a multidisciplinary perspective.
- Useful for hands-on learners with a focus on real-world applications.
Cons
- Outdated GitHub repository and parts list lead to practical challenges.
Product Price History
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BZD 132
Order now and get it around Sunday, June 28
This item is not restrict in my country.(Please click on above link if this item is not restrict in your country, So our team will review and allow.)
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Secured transaction
Ubuy works hard to protect your security and privacy. Our advanced payment security system ensures confidentiality by encrypting your information during transmission using AES (Advanced Encryption Standards) and SSL (Secure Socket Layer) protocols. Your payment details are 100% secure as we do not share your payment details with third party sellers.
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Features & Benefits
- Learn to build intelligent robots using AI, ROS 2, Python, and OpenCV.
- Gain a holistic understanding of robot design and task analysis.
- Implement AI/ML techniques for object detection and navigation.
- Create voice and natural language interactions for user engagement.
- Master neural networks and genetic algorithms for smart decision-making.
- Transform robots into helpful assistants capable of tackling real-world tasks.